README.md

metadata

title: Anything Detector
emoji: 🔍
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.49.1
python_version: '3.10'
app_file: app.py
pinned: false
startup_duration_timeout: 1h

🔍 Anything Detector

Custom object detection and counting without YOLO.

Workflow

1. Define classes in training/classes.txt.
2. Upload training images.
3. Select an image.
4. Draw bounding boxes directly on the image with the mouse.
5. Choose a class for each box.
6. Save annotations.
7. Train RT-DETR.
8. Upload new images and detect/count objects.

The annotation tool is implemented directly with HTML5 Canvas inside Gradio. It does not use the gradio_image_annotation package, avoiding the Node.js frontend dependency that can cause Space startup problems.

Example classes

cornetto
magnum
correto
cone
cup

Or anything else:

car
truck
person
dog
cat

Important

For production, attach persistent storage to the Space so the dataset and trained model survive rebuilds.

Startup fix

The annotation JavaScript is registered at the Gradio Blocks level rather than using the unsupported js_on_load argument on gr.HTML.

GPU

This Space is configured for Hugging Face ZeroGPU. GPU-dependent training and inference functions use @spaces.GPU; training runs synchronously inside the GPU allocation so a background thread cannot outlive the allocation.